我想加入来自Kafka制作者的两个流（json）。如果我过滤数据，代码就会工作。但当我加入他们的时候，它似乎不起作用。我想把加入的流打印到控制台上，但是什么也没有出现。这是我的密码

import java.util.Properties 
import org.apache.flink.streaming.api.scala._
import org.apache.flink.streaming.connectors.kafka.FlinkKafkaConsumer010
import org.apache.flink.streaming.util.serialization.SimpleStringSchema
import org.json4s._
import org.json4s.native.JsonMethods
import org.apache.flink.streaming.api.windowing.assigners.TumblingEventTimeWindows
import org.apache.flink.streaming.api.windowing.time.Time

object App {

def main(args : Array[String]) {

case class Data(location: String, timestamp: Long, measurement: Int, unit: String, accuracy: Double)
case class Sensor(sensor_name: String, start_date: String, end_date: String, data_schema: Array[String], data: Data, stt: Stt)

case class Datas(location: String, timestamp: Long, measurement: Int, unit: String, accuracy: Double)
case class Sensor2(sensor_name: String, start_date: String, end_date: String, data_schema: Array[String], data: Datas, stt: Stt)

val properties = new Properties();
    properties.setProperty("bootstrap.servers", "0.0.0.0:9092");
    properties.setProperty("group.id", "test");

    val env = StreamExecutionEnvironment.getExecutionEnvironment
    val consumer1 = new FlinkKafkaConsumer010[String]("topics1", new SimpleStringSchema(), properties)
   val stream1 = env
   .addSource(consumer1)

   val consumer2 = new FlinkKafkaConsumer010[String]("topics2", new SimpleStringSchema(), properties)
   val stream2 = env
   .addSource(consumer2)

   val s1 = stream1.map { x => {
     implicit val formats = DefaultFormats
     JsonMethods.parse(x).extract[Sensor]
     }
   }
   val s2 = stream2.map { x => {
     implicit val formats = DefaultFormats
     JsonMethods.parse(x).extract[Sensor2]
     }
   }

  val s1t = s1.assignAscendingTimestamps { x => x.data.timestamp }
  val s2t = s2.assignAscendingTimestamps { x => x.data.timestamp }

  val j1pre = s1t.join(s2t)
              .where(_.data.unit)
              .equalTo(_.data.unit)
              .window(TumblingEventTimeWindows.of(Time.seconds(2L)))
              .apply((g, s) => (s.sensor_name, g.sensor_name, s.data.measurement))
   env.execute()

}

}

我想问题出在时间戳的分配上。我认为 assignAscendingTimestamp 关于这两个来源是不正确的功能。
Kafka制作人制作的json有一个字段 data.timestamp 应该指定为时间戳。但我不知道该怎么办。
我还认为我应该给传入的元组一个时间窗口批处理（如在spark中）。但我不确定这是正确的解决方案。